---
title: "README"
author: "Isabelle Boulangeat"
date: "25/01/2021"
output:
  html_document:
    keep_md: yes
    variant: markdown_github
editor_options:
  chunk_output_type: console
always_allow_html: true
---

```{r setup, include=FALSE}
library(knitr)
# library(kableExtra)
knitr::opts_chunk$set(echo = TRUE)
# library(Jmisc)
library(tidyr)
sapply(list.files("R_fct"), function(x)source(paste0("R_fct/",x)))
data = readRDS("data.rds")

data$otable[which(is.na(data$otable$hauteur)),]

dat_h_veg = unique(merge(data$h, data$sites[,c("id_site", "ref_typoveg")], by.x = "ref_site", by.y ="id_site"))

length(unique(dat_h_veg$releve))
dim(dat_h_veg)

summary(dat_h_veg$hmean)

#==============================

library(dplyr)
# library(reshape)
library(tidyr)
library(ggplot2)

```

```{r ,fig=TRUE}

library(dplyr)
library(tidyr)
library(ggplot2)
dat_long <- dat_h_veg %>%
 select(hmean, hmad, ref_typoveg) %>%
 drop_na() %>%
 group_by(ref_typoveg) %>%
 summarize(hauteur=mean(hmean), var_inter=mad(hmean), var_intra = mean(hmad)) %>%
 gather(stat, value, hauteur:var_intra)

ggplot(dat_long, aes(fill=stat, x=ref_typoveg, y=value)) +
  geom_bar(position = "dodge", stat = "identity") +
  facet_wrap(~stat, ncol = 1, scales = "free")

```

```{r ,fig=TRUE}

## boxplot par milieu ##

ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean, na.rm=TRUE), y = hmean)) +
  geom_boxplot() +
  labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation")

```

```{r ,fig=TRUE}

## H series par milieu ##

pl <- ggplot(dat_h_veg, aes(x = date_releve, y = hmean)) +
  geom_line(aes(color = ref_site), show.legend = FALSE) +
  facet_wrap(~ref_typoveg)

pl + theme(legend.position = "none")


```

```{r ,fig=TRUE}
calage = read.csv("../PNE_calage_reformat.csv", sep= ";", dec = ",")
head(calage)
str(calage)
calage$releve = paste0(calage$site, calage$Releveur)

cal_mean = unique(calage %>% group_by(releve) %>% summarize(site = site, hmean = mean(hauteur, na.rm=TRUE)))

ggplot(cal_mean, aes(x = reorder(site, hmean), y = hmean)) +
  geom_boxplot() +
  geom_point() 

obs_error = cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean), hmad_st = mad(hmean)/mean(hmean), hm = mean(hmean))


```

```{r ,fig=TRUE}
ggplot(obs_error, aes(x = reorder(site, hm), y = hmad_st)) +
  geom_bar(stat = "identity")

```

```{r ,fig=TRUE}
### sd vs mad
ggplot(dat_h_veg, aes(x = hmad, y = hsd)) +
  geom_point() 

```

```{r ,fig=TRUE}
### dans le temps
ggplot(dat_h_veg, aes(x = date_releve, y = hmad)) +
  geom_line(aes(color = ref_site), show.legend = FALSE) +
  facet_wrap(~ref_typoveg)

## boxplot par milieu ##

```

```{r ,fig=TRUE}
ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad, na.rm=TRUE), y = hmad)) +
  geom_boxplot() +
  labs(y="Variation intra de hauteur", x="Type vegetation")

```

```{r ,fig=TRUE}
ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad/hmean, na.rm=TRUE), y = hmad/hmean)) +
  geom_boxplot() +
  labs(y="Variation intra de hauteur (stand. moy.)", x="Type vegetation")

```